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Author SHA1 Message Date
Glenn Jocher 9c776b8052 updates 2019-07-14 21:38:55 +02:00
Glenn Jocher 3fc676b28a updates 2019-07-14 11:29:07 +02:00
Glenn Jocher 831b6e39b6 updates 2019-07-12 17:02:04 +02:00
Glenn Jocher 03c6fe1ffe updates 2019-07-12 16:10:37 +02:00
Glenn Jocher 0aa9759a90 updates 2019-07-12 15:44:39 +02:00
Glenn Jocher bb38391342 updates 2019-07-12 14:28:46 +02:00
Glenn Jocher bd9789aa00 equal layer weights 2019-07-12 12:23:17 +02:00
Glenn Jocher 5886200401 updates 2019-07-12 01:19:32 +02:00
Glenn Jocher a2909c59f8 updates 2019-07-11 11:57:10 +02:00
Glenn Jocher b005a17eff updates 2019-07-11 11:56:46 +02:00
Glenn Jocher 3373006d0e updates 2019-07-10 22:11:48 +02:00
Glenn Jocher 4f6ef59d92 updates 2019-07-10 20:47:05 +02:00
Glenn Jocher a9e42a16f1 updates 2019-07-10 19:48:29 +02:00
Glenn Jocher bb1e551150 updates 2019-07-08 19:26:46 +02:00
Glenn Jocher 0bd763f528 updates 2019-07-08 18:32:31 +02:00
Glenn Jocher feeaf734f2 updates 2019-07-08 18:04:44 +02:00
Glenn Jocher da9ec7d12f updates 2019-07-08 18:00:19 +02:00
Glenn Jocher 60bc2c1fbd updates 2019-07-08 15:43:46 +02:00
Glenn Jocher 94669fb704 updates 2019-07-08 15:24:20 +02:00
Glenn Jocher 291c3ec9c7 updates 2019-07-08 15:02:20 +02:00
glenn-jocher 70f6379601 GIoU to default 2019-07-07 23:24:34 +02:00
glenn-jocher 32a52dfb02 GIoU to default 2019-07-05 12:33:37 +02:00
glenn-jocher 429bd3b8a9 GIoU to default 2019-07-05 11:41:43 +02:00
glenn-jocher b649a95c9a GIoU to default 2019-07-05 00:36:37 +02:00
glenn-jocher abf59f1565 updates 2019-07-04 22:10:46 +02:00
glenn-jocher d0eace6cec updates 2019-07-04 21:34:33 +02:00
glenn-jocher 109991198c updates 2019-07-03 16:18:08 +02:00
glenn-jocher 1e62ee2152 updates 2019-07-03 16:17:46 +02:00
glenn-jocher ab141fcc1f updates 2019-07-03 15:37:04 +02:00
glenn-jocher a8cf64af31 updates 2019-07-02 18:21:28 +02:00
Yonghye Kwon ccf757b3ea changed the criteria for the best weight file (#356) 
* changed the criteria for the best weight file

changed the criteria for the best weight file from loss to mAP

I trained the model on my custom dataset. But I failed to get a good results when I load the weight file that has the lowest loss on test dataset. 

I thought that the loss used in YOLO is not proper criteria for detection performance. So I changed the criteria from loss to mAP.

what do you think of this?

* Update train.py
 2019-07-02 12:24:18 +02:00
glenn-jocher 1fd871abd8 updates 2019-07-01 17:44:42 +02:00
glenn-jocher f43ee6ef94 updates 2019-07-01 17:17:29 +02:00
glenn-jocher cf51cf9c99 updates 2019-07-01 17:14:42 +02:00
glenn-jocher 05358accbb updates 2019-07-01 15:23:30 +02:00
glenn-jocher c4409aa2ed updates 2019-07-01 15:22:22 +02:00
glenn-jocher b0d62e5204 updates 2019-07-01 15:21:06 +02:00
glenn-jocher 5e2b802f68 updates 2019-07-01 14:48:44 +02:00
glenn-jocher 63036deeb7 updates 2019-07-01 00:41:13 +02:00
glenn-jocher 32f5ea955b updates 2019-06-30 17:47:10 +02:00
glenn-jocher db2674aa31 updates 2019-06-30 17:34:29 +02:00
glenn-jocher 388b66dcd0 updates 2019-06-30 15:24:34 +02:00
Glenn Jocher 45540c787f updates 2019-06-25 19:36:11 +02:00
Glenn Jocher 1d76751e1f updates 2019-06-25 12:37:24 +02:00
Glenn Jocher e4cc830690 updates 2019-06-25 12:21:27 +02:00
Glenn Jocher 9a56d97059 updates 2019-06-25 11:54:19 +02:00
Glenn Jocher 6b222df35d updates 2019-06-24 15:56:20 +02:00
Glenn Jocher d208f006a1 updates 2019-06-24 14:46:00 +02:00
Glenn Jocher 0005823d1f updates 2019-06-24 13:43:17 +02:00
Glenn Jocher 57b616b8b1 updates 2019-06-23 22:01:11 +02:00